The granitoid massifs of Kashan 1:100000 sheet and related skarns are located in the magmatic-plutonic belt of Orumieh-Dokhtar and between the zones of Sanandaj-Sirjan and Central Iran. These intrusive masses with granodiorite-tonalite composition penetrated the Middle Mycenaean period from northwest of Kashan to the south of Ghahroud village in a series of shales and Jurassic sandstones, limestone and Cretaceous and Eocene marls. They caused Adjacent metamorphism to the surrounding rocks and the formated skarns, marble, quartzite and hornfels. Kashan region located in the northeast of Isfahan is a suitable area for exploration of metal minerals. Important criteria of iron skarn ore mining can be seen in this area. The most important of these criteria are the presence of thermal metamorphic due to plutonic infiltration masses and structural complications such as lineation and faults. In this research, ASTER and SENTINEL-2A satellite data have been used to highlight the alterations in the field samples. Initially, the ASTER image resolution was increased to 10 meter by SENTINEL-2A images, by various methods such as false color composite, spectral angle mapper (SAM), mixture tuned matched filter (MTMF), and Linear spectral unmixing (LSU) alterations of index minerals have been highlighted. The results of satellite image processing were controlled using spectroscopic and field studies. According to the results of remote sensing, MTMF method as a sub-pixel method has the highest degree of adaptation compared to SAM and LSU methods and has identified alterations more accurately. Also, increasing the resolution of ASTER images by SENTINEL-2A has improved the performance of the methods used. In order to determine the mineralogical characteristics of field samples, thin and polished sections were prepared. Also, the spectral characteristics of the samples were measured using FieldSpec4 spectrometer and then extracted using RS3 software. In geophysical studies, 7.5 km airborne magnetic data were used to identify large intrusive masses and their boundaries with iron skarn ore mining units. In these studies, reduced to pole (RTP), upward continuation, first vertical derivative and analytical signal methods were used. The methods of reduced to pole and the analytical signal had the highest degree of Conformity with the mineral area and indices. In geochemical studies, hopeful areas were determined by studying the true catchment basin area and using factor analysis of normal data and Geochemical Mineralization Probability Index (GMPI). Prediction-area diagram (P-A) was used to quantitatively evaluate the results of geochemical studies. According to the prediction-area diagram, the combined method of stepwise factor analysis and GMPI improved the results compared to conventional factor analysis, so that in a smaller area of catchments, more areas of skarn iron were identified. Structural features were also developed by geological map. Finally, various information layers including metamorphism maps, geological maps, faults and geochemical and geophysical anomalies maps in ArcMap10.5 software using fuzzy Analytical Hierarchy method to prepare iron skarn mineral potential maps were integrated. The fuzzy analytic hierarchical method, while significantly reducing the exploration area, identified six of the seven area of skarn iron. In order to reduce the uncertainty of the fuzzy analytic Hierarchy method, a sensitivity analysis was performed. The results of sensitivity analysis showed that by changing the scores of criteria and options, the prioritization of layers was not the same but the first priority of each criterion did not change.